An Internet of Things based Solar Power Monitoring System using Node MCU

Solar power systems are increasingly being adopted as a renewable energy solution worldwide. However, effective monitoring and management of these systems are crucial for optimizing their performance and ensuring their reliable operation. In this research paper, we propose a solar power monitoring system using NodeMCU, an open-source IoT platform. Our system collects, processes, and visualizes real-time data from solar panels, batteries, and other qsystem components, providing comprehensive monitoring capabilities for solar power system owners. The system is designed to be cost-effective and scalable, making it suitable for both residential and commercial applications. Through our research, we demonstrate the feasibility and effectiveness of our solar power monitoring system using NodeMCU. The findings contribute to the field of renewable energy management by offering an innovative approach to monitor and optimize solar power systems, promoting the wider adoption of renewable energy sources for a sustainable future

Smart Pumping System using Energy Efficiency Control Algorithm

Water is one of the most important resources for sustaining life on earth. It is essential for daily activities like cooking, cleaning, and bathing. In residential areas, water supply systems are usually managed by Municipal Corporations or other governing bodies. This project mainly focuses on the IoT based solution for automation of the water tank filling system in our residential area. In this project two Esp8266 MCU connected to the same cloud channel are used, one will be at the Water Source side and other will be at Tank side. The Ultrasonic Sensor connected to the Esp8266 senses the water level in the tank, if the Water level is low the Esp8266 will sent the Motor ON signal to the ThingSpeak IoT Cloud and the Esp8266 at the river or dam side is also connected to the same cloud channel will read that signal and turn the ‘Motor ON’. If the tank is full the Esp8266 sends the ‘Motor OFF signal’ over the cloud and the other microcontroller at the river/dam side will turn OFF the motor. A web interface displaying graphs and indicators is also provided for the user to study and analyze the data from the system

A Smart System for Detection of Road Lane and Divider

Road Lane and divider detection is a core part in environmental perception for driver assistance system. The paper discusses about machine learning and computer vision approach to identify road lanes and dividers and proposes a system for detection of road lane and divider. Driving assistance systems heavily rely on the road lane and divider recognition. Voting classification was implemented using 7 different classifiers. The combination of Scale Invariant Feature Transform (SIFT) and Oriented FAST and Rotated BRIEF (ORB) provided feature extraction. Principle Component Analysis (PCA) provided dimension reduction. The performance has been examined on the basis of accuracy (95.50%), precision (78.81%), recall (65.71%), and F1 score (71.67%). The proposed solution is helpful in solving issues related to road safety and reducing road accidents

Smart ATM Security and Alert System with Real-Time Monitoring

The growing adoption of automated teller machines (ATMs) worldwide, ensuring the security of ATM transactions and protecting customer data has become a critical concern for the banking industry. In this research paper, we proposed an Internet of Things (IoT) based ATM security system using the NodeMCU ESP8266 module, PIR (Passive Infrared) sensor, LCD display with I2C interface, and the Telegram app. The proposed system utilizes the NodeMCU ESP8266 module, which is a low-cost Wi-Fi enabled microcontroller, as the main controller for the security system. The PIR sensor is used to detect motion or presence near the ATM, which can potentially indicate unauthorized access. The LCD display with I2C interface is used to provide real-time status information about the ATM, such as Motion Detected or NO Motion. When the PIR sensor detects any suspicious activity near the ATM, the NodeMCU ESP8266 module sends a notification to the ATM owner or security personnel via the Telegram app. The notification includes details about the detected activity, allowing the owner or security personnel to take immediate action. The real- time alerts enable prompt response to potential security breaches and help prevent unauthorized access to the ATM

PerceptGuide: A Perception Driven Assistive Mobility Aid Based on Self-Attention and Multi-Scale Feature Fusion

The paper introduces a novel wearable aid, PerceptGuide to help for visually impaired individuals to perceive scene around them. It is designed as a wearable, light weight chest rig bag, that incorporates a monocular camera, ultrasonic sensors, vibration motors, and a mono-earphone, powered by an embedded Nvidia Jetson development board. The system provides directional obstacle alerts through the vibration motors, allowing users to avoid obstacles on their path. A user-friendly push-button enables user to inquire about scene information in front of them. The scene details are effectively conveyed through a novel scene understanding approach, that combines multi-scale feature fusion, self-attention models, and a multilayer GRU (Gated Recurrent Unit) architecture on the ResNet50 backbone. The proposed system generates coherent and descriptive captions by capturing image features at different scales, enhancing the quality and contextual understanding of the scene details. The self-attention in both the encoder (ResNet50 + Feature fusion model) and decoder (multilayer GRU), effectively captures long-range dependencies and attend to relevant image regions. The quantitative evaluations conducted on the MSCOCO and Flicker8k datasets show the effectiveness of the model with improved Bleu-67.7, RougeL – 47.6, Meteor – 22.7 and CIEDR-67.4 scores. The PerceptGuide system exhibits exceptional real-time performance, generating audible captions in just 1.5 to 2 seconds. This rapid response time significantly aids visually impaired individuals in understanding the scenes around them. The qualitative evaluation of the aid emphasizes its real-time performance, demonstrating the generation of context-aware, semantically meaningful captions. This validates its potential as a wearable assistive aid for visually impaired people, with the added advantages of low power consumption, compactness, and a lightweight design

A Qualitative and Quantitative Analysis of Research in Mobility Technologies for Visually Impaired People

Assistive technology in rehabilitation programs is vital for people with vision impairments worldwide. The term “blind assistive technology” refers to mobility devices specifically designed to provide position, orientation and mobility assistance for visually impaired individuals during indoor and outdoor activities. The paper presents a comprehensive evaluation of 140 research articles published over the past 75 years (1946 to 2022). This research analyses the evolution of assistive technology aids in depth, in terms sensing technique followed, algorithms employed for obstacle detection, localization, object recognition, depth estimation and scene understanding. It also includes, the functional attributes of the aid, feedback type, and assistive solutions embedded in aid. It evaluates the assistive aids for their usability index, portability, battery life, feedback type, and aesthetics. The survey findings reveal that optical and sonic sensor-based aids prioritize speed, weight, and battery life but lack major functionalities, achieving an average performance score of 62%. Stereo, monocular, SLAM, and 3-D point cloud-based aids excel in obstacle distance estimation and avoidance but require greater memory resources, with a lower performance score of 41%. Artificial intelligence and cloud-based aids offer comprehensive scene details but demand complex computational capabilities, achieving a performance score of 44%. However, the most suitable technology for developing state-of-the-art solutions for blind individuals is the multisensor fusion-based and guide robot-based aids, providing a majority of the essential assistive functions with a performance score of 51%. The study highlights possible challenges associated with implementing assistive technology aids, emphasizes the importance of user acceptability, and stresses the need for real-time evaluation of blind aids. The paper lays a concrete foundation and direction for future development, emphasizing the critical challenges faced by blind users, including boarding trains, traveling on public transport, shopping in a supermarket, avoiding dynamic obstacles, and real-time understanding of the surrounding scene. Addressing these key concerns is crucial for the continued development and improvement of assistive technology aids for the visually impaired, leading to enhanced independence, mobility, and ultimately, a higher quality of life